Distributed mobile microphone arrays for robot navigation and acoustic source localization

Abstract

In distributed microphone arrays, each microphone is connected to a separate recording device, which requires compensation for their different clock shifts. In this paper, we propose a new type of distributed arrays, in which the microphones are moving. This mobility introduces innovation that can be used to estimate the positions of both the sound sources and the microphones, as well as compensate for the clock shifts. Estimation is done using extended Kalman filters with heuristics that improve the convergence.We discuss the proposed method in the context of mobile robotics: each microphone is attached to a controllable mobile robot. In this scenario, the array can be used to localize soundemitting objects in the robot's environment, while providing information about robots' positions. Results show that the error of estimating robots' positions is as low as 5 cm with the source source localization error of 6 mm and the clock synchronization error of 178 μs, for the case of 9 microphones and 5 sound sources.

Distributed acoustic slam

“…The speed of sound was assumed to be 343 m/s. The tests were run multiple times for (2,4,8,12) sound sources and (2,5,8,10,12,14) robots. Process noise for the robot state transition was N (0, σ 2 xy ) for position and N (0, σ 2 ϕ ) for orientation, where σ xy was 10 cm and σ ϕ was 1 deg.…”

“…In DASLAM, we use a distributed mobile microphone array, which is defined as in [12]: 1. There are N sound sources and M microphones, all at arbitrary positions.…”

“…In this paper we extend on this work and introduce microphone mobility and increase the number of sound sources to an arbitrary number. Furthermore, due to high non-linearity of the system, we employ particle filters, which we have found to be much more stable and accurate than the EKF used in [8,10,12]. We apply this technique to DASLAM.…”